New ST-segment elevation myocardial infarction criteria for left bundle branch block based on QRS area
Richard E Gregg1, Eric D Helfenbein, Saeed Babaeizadeh
1Advanced Algorithm Research Center, Philips Healthcare, Andover, MA, USA.
Insights
A new algorithm using QRS area improves ST-segment elevation myocardial infarction (STEMI) detection in left bundle-branch block (LBBB) by enhancing sensitivity. Different algorithms offer trade-offs between sensitivity and specificity for STEMI diagnosis in LBBB patients.
Area of Science:
- Cardiology
- Medical Imaging
- Algorithm Development
Background:
- Detecting ST-segment elevation myocardial infarction (STEMI) with left bundle-branch block (LBBB) on ECG is challenging due to altered conduction causing ST deviation.
- Existing algorithms for STEMI detection in LBBB have limitations in balancing sensitivity and specificity.
Purpose of the Study:
- To introduce a novel algorithm for STEMI detection in the presence of LBBB.
- To compare the performance of the new algorithm against three established criteria: Sgarbossa, Selvester 10% RS, and Smith 25% S-wave.
Main Methods:
- The study analyzed ECG data from 143 acute myocardial infarction (MI) patients and 239 controls, with LBBB identified by computer interpretation.
- A new algorithm utilizing an ST threshold based on QRS area was developed and compared with Sgarbossa, Selvester, and Smith criteria.
- Performance was evaluated using sensitivity, specificity, and positive likelihood ratio (LR+), with variations tested for single and 2-lead requirements.
Main Results:
- Algorithm performance varied, with the Sgarbossa score (≥3) showing the lowest sensitivity (13.3%) and highest specificity (97.9%).
- The Selvester 10% rule demonstrated the highest sensitivity (30.1%) but lower specificity (93.2%).
- The novel Philips QRS area (23.8% sensitivity, 95.8% specificity) and Smith S-wave (20.3% sensitivity, 94.9% specificity) algorithms performed intermediately.
Conclusions:
- Discordant ST elevation criteria enhance STEMI detection sensitivity in LBBB but can reduce specificity.
- The Selvester algorithm is preferable for applications prioritizing high sensitivity in STEMI detection.
- For scenarios demanding low false positive rates, such as pre-hospital activation for urgent PCI, the Philips QRS area or Smith 25% S-wave algorithms may be more suitable.
Background:
ECG detection of ST-segment elevation myocardial infarction (STEMI) in the presence of left bundle-branch block (LBBB) is challenging due to ST deviation from the altered conduction. The purpose of this study was to introduce a new algorithm for STEMI detection in LBBB and compare the performance to three existing algorithms.
Methods:
Source data of the study group (143 with acute MI and 239 controls) comes from multiple sources. ECGs were selected by computer interpretation of LBBB. Acute MI reference was hospital discharge diagnosis. Automated measurements came from the Philips DXL algorithm. Three existing algorithms were compared, (1) Sgarbossa criteria, (2) Selvester 10% RS criteria and (3) Smith 25% S-wave criteria. The new algorithm uses an ST threshold based on QRS area. All algorithms share the concordant ST elevation and anterior ST depression criteria from the Sgarbossa score. The difference is in the threshold for discordant ST elevation. The Sgarbossa, Selvester, Smith and Philips discordant ST elevation criteria are (1) ST elevation ≥ 500 μV, (2) ST elevation ≥ 10% of |S|-|R| plus STEMI limits, (3) ST elevation ≥ 25% of the S-wave amplitude and (4) ST elevation ≥ 100 μV + 1050 μV/Ash * QRS area. The Smith S-wave and Philips QRS area criteria were tested using both a single and 2 lead requirement. Algorithm performance was measured by sensitivity, specificity, and positive likelihood ratio (LR+).
Results:
Algorithm performance can be organized in bands of similar sensitivity and specificity ranging from Sgarbossa score ≥ 3 with the lowest sensitivity and highest specificity, 13.3% and 97.9%, to the Selvester 10% rule with the highest sensitivity and lower specificity of 30.1% and 93.2%. The Smith S-wave and Philips QRS area algorithms were in the middle band with sensitivity and specificity of (20.3%, 94.9%) and (23.8%, 95.8%) respectively.
Conclusion:
As can be seen from the difference between Sgarbossa score ≥ 3 and other algorithms for STEMI in LBBB, a discordant ST elevation criterion improves the sensitivity for detection but also results in a drop in specificity. For applications of automated STEMI detection that require higher sensitivity, the Selvester algorithm is better. For applications that require a low false positive rate such as relying on the algorithm for pre-hospital activation of cardiac catheterization laboratory for urgent PCI, it may be better to use the 2 lead Philips QRS area or Smith 25% S-wave algorithm.
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